Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A data processing method performed in a computer having a memory for determining six parameters of a contact position of a physiological or artificial joint which connects two bones, wherein the contact position is a relative position between the two bones in which physiological or artificial surfaces defined at ends of the two bones respectively by the bones or by implants carried on the bones are in contact with each other, and wherein three of the parameters define a translational shift and three of the parameters define a rotational shift, the method comprising: acquiring a plurality of sample contact position datasets, each dataset comprising six parameters that correspond to the six parameters describing the contact position; acquiring a subset of n of the parameters of the contact position as an input parameter dataset; selecting at least two of the sample contact position datasets based on the input parameter dataset; and determining the m=6−n remaining parameters of the contact position based on the at least two selected sample contact position datasets.
A computer-based method determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones. The contact position is the relative position where surfaces of the bones (or implants on the bones) touch. Three parameters define translational shift, and three define rotational shift. The method acquires multiple sample datasets, each containing these six parameters. It then acquires a subset (n) of these parameters as input. At least two sample datasets are selected based on the input parameters, and the remaining m=6-n parameters are determined using these selected datasets.
2. The method of claim 1 , wherein the remaining parameters are determined by interpolation or extrapolation.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, and wherein the remaining parameters are determined by interpolation or extrapolation. This means the missing parameters are estimated based on the known parameters of the selected sample datasets, using techniques to find values between or beyond the known data points.
3. The method according to claim 2 , wherein the interpolation is a spline interpolation or uses inverse distance weighting.
The method of claim 2, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein determining remaining parameters by interpolation or extrapolation uses spline interpolation or inverse distance weighting. Spline interpolation fits smooth curves through the data points, while inverse distance weighting assigns weights to the sample points based on their distance to the unknown point.
4. The method according to claim 1 , wherein the selected sample contact position datasets correspond to sample contact positions which are, regarding the input parameters, the nearest neighbors of the contact position.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein the selected sample contact position datasets correspond to sample contact positions which are, regarding the input parameters, the nearest neighbors of the contact position. This means the method chooses the sample datasets that are most similar to the input parameters, effectively finding the closest matches in the sample data.
5. The method of claim 4 , wherein a distance between the contact position and a sample contact position is calculated using a Minkowski distance function.
The method of claim 4, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein the selected sample contact positions are the nearest neighbors, and a distance between the contact position and a sample contact position is calculated using a Minkowski distance function. This function quantifies the similarity between the input parameters and the sample datasets, allowing the method to select the closest matches numerically.
6. The method according to claim 1 , wherein the sample contact position datasets are arranged in an n-dimensional array and each array entry comprises the m remaining parameters.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein the sample contact position datasets are arranged in an n-dimensional array and each array entry comprises the m remaining parameters. This organizes the sample data for efficient searching, where 'n' is the number of input parameters, and each point in the array directly stores the calculated remaining parameters.
7. The method according to claim 1 , wherein the sample contact positions are arranged at equidistant intervals.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein the sample contact positions are arranged at equidistant intervals. This means the sample datasets are evenly spaced across the range of possible input parameter values, allowing for simpler indexing and interpolation.
8. The method according to claim 1 , wherein a sample contact position dataset is void for an impossible joint contact position.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein a sample contact position dataset is void for an impossible joint contact position. This allows the method to represent and exclude physically unrealistic or forbidden joint configurations from the sample data.
9. The method of claim 1 , wherein a sample contact position dataset further comprises affiliate information which indicates that the sample contact position belongs to a contact profile of contact positions.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein a sample contact position dataset further comprises affiliate information which indicates that the sample contact position belongs to a contact profile of contact positions. This means the sample datasets can be grouped into related sets, such as representing the motion path of a joint during a specific activity.
10. The method according to claim 1 , wherein the step of determining the m=6−n remaining parameters of the contact position is repeated for a sequence of input parameter datasets, thus resulting in a sequence of contact positions.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein the step of determining the m=6−n remaining parameters of the contact position is repeated for a sequence of input parameter datasets, thus resulting in a sequence of contact positions. This allows the method to track the joint's movement over time or across a range of configurations, generating a series of contact positions.
11. The method according to claim 1 , wherein a sample position dataset is determined by virtually positioning three-dimensional images of the two bones such that they are in contact and using the relative position of the bones thus positioned as a sample contact position.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein a sample position dataset is determined by virtually positioning three-dimensional images of the two bones such that they are in contact and using the relative position of the bones thus positioned as a sample contact position. The sample data is created by simulating the joint contact within a virtual environment, extracting the relative position and orientation of the bones in that configuration.
12. The method according to claim 1 , wherein a sample position dataset is automatically determined by using collision detection of three-dimensional models of the two bones.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein a sample position dataset is automatically determined by using collision detection of three-dimensional models of the two bones. The sample data is created automatically by detecting when 3D models of the bones collide in a simulation, representing a point of contact.
13. The method according to claim 1 , wherein a sample position dataset is determined by measuring a real joint.
The method of claim 1, a computer-based method that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones, wherein a sample position dataset is determined by measuring a real joint. The sample data is acquired from a physical joint through sensors or measurement devices to determine the position and orientation during contact.
14. A computer program embodied on a non-transitory computer readable medium which, when running on a computer or when loaded onto a computer, causes the computer to determine six parameters of a contact position of a physiological or artificial joint which connects two bones, wherein the contact position is a relative position between the two bones in which physiological or artificial surfaces defined at ends of the two bones respectively by the bones or by implants carried on the bones are in contact with each other, and wherein three of the parameters define a translational shift and three of the parameters define a rotational shift, by performing steps comprising: acquiring a plurality of sample contact position datasets, each dataset comprising six parameters that correspond to the six parameters describing the contact position; acquiring a subset of n of the parameters of the contact position as an input parameter dataset; selecting at least two of the sample contact position datasets based on the input parameter dataset; and determining the m=6-n remaining parameters of the contact position based on the at least two selected sample contact position datasets.
A computer program stored on a non-transitory medium determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones. The contact position is the relative position where surfaces of the bones (or implants on the bones) touch. Three parameters define translational shift, and three define rotational shift. The program acquires multiple sample datasets, each containing these six parameters. It then acquires a subset (n) of these parameters as input. At least two sample datasets are selected based on the input parameters, and the remaining m=6-n parameters are determined using these selected datasets.
15. A computer on which the computer program according to claim 14 is running or into the memory of which the computer program is loaded.
A computer running the program described in claim 14, a program that determines the six parameters defining the contact position of a physiological or artificial joint connecting two bones. This claim covers the physical computer executing the software that calculates joint contact parameters.
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December 26, 2017
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